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Genius Business Solutions

Genius Business Solutions

via ZipRecruiter

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Senior Data Engineer & Technical Lead | Auburn Hill, MI | 6+ Months

Anywhere
Full-time
Posted 12/5/2025
Verified Source
Key Skills:
Python
PySpark
Airflow
CI/CD
Docker
Git
SQL
Unix/Linux
Test-Driven Development

Compensation

Salary Range

$120K - 160K a year

Responsibilities

Design, develop, and maintain scalable data pipelines and CI/CD processes while leading and mentoring engineers in a data engineering environment.

Requirements

7+ years IT experience with 5+ years in data engineering using Python and PySpark, Airflow expertise, CI/CD pipeline development, cloud/container experience, and strong collaboration skills.

Full Description

About Genius Business Solutions Inc. (GBSI) Featured in CNBC, Digital Journal, Fox News, and CIO Review, Genius Business Solutions Inc. (GBSI) is a globally recognized IT services leader with 20+ years of experience serving Fortune 500 organizations. Our teams deliver cutting-edge solutions across industries such as Healthcare, Life Sciences, Automotive, Manufacturing, and Consumer Goods — helping clients transform business processes through innovation and technology. Position Overview The Senior Data Engineer & Technical Lead (SDET Lead) will play a pivotal role in delivering major data engineering initiatives within the Data & Advanced Analytics space. This position requires hands-on expertise in building, deploying, and maintaining robust data pipelines using Python, PySpark, and Airflow, as well as designing and implementing CI/CD processes for data engineering projects Key Responsibilities 1. Data Engineering: Design, develop, and optimize scalable data pipelines using Python and PySpark for batch and streaming workloads. 2. Workflow Orchestration: Build, schedule, and monitor complex workflows using Airflow, ensuring reliability and maintainability. 3. CI/CD Pipeline Development: Architect and implement CI/CD pipelines for data engineering projects using GitHub, Docker, and cloud-native solutions. 4. Testing & Quality: Apply test-driven development (TDD) practices and automate unit/integration tests for data pipelines. 5. Secure Development: Implement secure coding best practices and design patterns throughout the development lifecycle. 6. Collaboration: Work closely with Data Architects, QA teams, and business stakeholders to translate requirements into technical solutions. 7. Documentation: Create and maintain technical documentation, including process/data flow diagrams and system design artifacts. 8. Mentorship: Lead and mentor junior engineers, providing guidance on coding, testing, and deployment best practices. 9. Troubleshooting: Analyze and resolve technical issues across the data stack, including pipeline failures and performance bottlenecks. Cross-Team Knowledge Sharing: Cross-train team members outside the project team (e.g., operations support) for full knowledge coverage. Includes all above skills, plus the following; · Minimum of 7+ years overall IT experience · Experienced in waterfall, iterative, and agile methodologies Experience - 1. Hands-on Data Engineering: Minimum 5+ years of practical experience building production-grade data pipelines using Python and PySpark. 2. Airflow Expertise: Proven track record of designing, deploying, and managing Airflow DAGs in enterprise environments. 3. CI/CD for Data Projects: Ability to build and maintain CI/CD pipelines for data engineering workflows, including automated testing and deployment**. 4. Cloud & Containers: Experience with containerization (Docker and cloud platforms (GCP) for data engineering workloads. Appreciation for twelve-factor design principles 5. Python Fluency: Ability to write object-oriented Python code manage dependencies, and follow industry best practices 6. Version Control: Proficiency with **Git** for source code management and collaboration (commits, branching, merging, GitHub/GitLab workflows). 7. Unix/Linux: Strong command-line skills** in Unix-like environments. 8. SQL: Solid understanding of SQL for data ingestion and analysis. 9. Collaborative Development: Comfortable with code reviews, pair programming and using remote collaboration tools effectively. 10. Engineering Mindset: Writes code with an eye for maintainability and testability; excited to build production-grade software 11. Education: Bachelor's or graduate degree in Computer Science, Data Analytics or related field, or equivalent work experience. Unique Skills • Graduate degree in a related field, such as Computer Science or Data Analytics • Familiarity with Test-Driven Development (TDD) • A high tolerance for OpenShift, Cloudera, Tableau, Confluence, Jira, and other enterprise tools. Equal Employment Opportunity GeniusBSI is an Equal Opportunity Employer. We believe that no one should be discriminated against because of their differences, such as age, disability, ethnicity, gender, gender identity and expression, religion, or sexual orientation. All employment decisions are made without regard to any legally protected characteristics.

This job posting was last updated on 12/10/2025

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